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Related Concept Videos

Peptide Identification Using Tandem Mass Spectrometry01:33

Peptide Identification Using Tandem Mass Spectrometry

Tandem mass spectrometry, also known as MS/MS or MS2, is an analytical technique that employs two mass analyzers. Essentially it is a series of mass spectrometers that helps isolate a particular biomolecule and then helps study its chemical properties.
This technique helps gather information regarding the protein from which the peptide was obtained and to study the peptides’ amino acid sequence. Identifying peptides from a complex mixture is an important component of the growing field of...
Proteomics01:33

Proteomics

A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term proteomics...

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Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools
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MassSieve: panning MS/MS peptide data for proteins.

Douglas J Slotta1, Melinda A McFarland, Sanford P Markey

  • 1Laboratory of Neurotoxicology, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA. slottad@ncbi.nlm.nih.gov

Proteomics
|June 22, 2010
PubMed
Summary

MassSieve is a Java platform for analyzing LC-MS/MS data from multiple search engines. It helps visualize and evaluate large datasets, improving peptide identification and coverage in proteomics research.

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Area of Science:

  • Proteomics
  • Bioinformatics
  • Computational Biology

Background:

  • Mass spectrometry-based proteomics generates large datasets.
  • Evaluating results from multiple search engines is challenging.
  • Existing tools may not adequately handle diverse search characteristics.

Purpose of the Study:

  • Introduce MassSieve, a Java platform for LC-MS/MS data analysis.
  • Facilitate visualization and parsimony analysis of search engine results.
  • Address the need for tools to manage increasing proteomic data sizes.

Main Methods:

  • Developed a Java-based software platform named MassSieve.
  • Integrated support for results from various LC-MS/MS database search engines.
  • Implemented visualization and parsimony analysis functionalities.

Main Results:

  • MassSieve enables merging and evaluation of data from multiple search engines.
  • The platform supports differing search characteristics, enhancing analysis.
  • Facilitates increased peptide sequence coverage and identification of ambiguous assignments.

Conclusions:

  • MassSieve provides a valuable tool for proteomics researchers.
  • The platform aids in the interpretation of complex LC-MS/MS data.
  • Enhances the efficiency and accuracy of shotgun proteomic experiment analysis.